BACKGROUND AND AIM: To assess the clinical and economic outcomes of non-invasive testing strategies in the diagnosis of significant liver fibrosis (Metavir score >or= 2) compared with liver biopsy. METHODS: We developed a decision analytic model of non-invasive testing strategies in a hypothetical patient population with genotype 1 hepatitis C virus infection, with no contraindications to liver biopsy. The testing strategies included a testing algorithm using the Fibrosure test, a non-invasive measure of fibrosis, followed by liver biopsy for patients with indeterminate results, Fibrospect II, and Fibroscan. The primary outcomes were sensitivity, specificity, diagnostic accuracy (true positive + true negatives/total patients), and costs, evaluated from the health-care payer perspective. RESULTS: The testing algorithm using Fibrosure was the most accurate non-invasive strategy with a sensitivity, specificity, and overall accuracy of 84%, 87%, and 86%, respectively. In comparison with liver biopsy alone, there was a cost savings of approximately $770/person with the Fibrosure testing algorithm, but a net decrease in accuracy of 14%. Fibrospect II and Fibroscan had poorer accuracy (decreases of 12% and 4%, respectively) and lower costs (-$138 and -$357, respectively) compared with the Fibrosure algorithm. In uncertainty analyses in which biopsy sampling error was considered, the Fibrosure algorithm remained consistently less accurate (5-14% decrease). CONCLUSIONS: The results of our study suggest that compared with liver biopsy, non-invasive testing algorithms can result in short-term cost savings, but the consequences of misdiagnosis in terms of health outcomes and treatment costs might outweigh the short-term gains in cost and convenience.
BACKGROUND AND AIM: To assess the clinical and economic outcomes of non-invasive testing strategies in the diagnosis of significant liver fibrosis (Metavir score >or= 2) compared with liver biopsy. METHODS: We developed a decision analytic model of non-invasive testing strategies in a hypothetical patient population with genotype 1 hepatitis C virus infection, with no contraindications to liver biopsy. The testing strategies included a testing algorithm using the Fibrosure test, a non-invasive measure of fibrosis, followed by liver biopsy for patients with indeterminate results, Fibrospect II, and Fibroscan. The primary outcomes were sensitivity, specificity, diagnostic accuracy (true positive + true negatives/total patients), and costs, evaluated from the health-care payer perspective. RESULTS: The testing algorithm using Fibrosure was the most accurate non-invasive strategy with a sensitivity, specificity, and overall accuracy of 84%, 87%, and 86%, respectively. In comparison with liver biopsy alone, there was a cost savings of approximately $770/person with the Fibrosure testing algorithm, but a net decrease in accuracy of 14%. Fibrospect II and Fibroscan had poorer accuracy (decreases of 12% and 4%, respectively) and lower costs (-$138 and -$357, respectively) compared with the Fibrosure algorithm. In uncertainty analyses in which biopsy sampling error was considered, the Fibrosure algorithm remained consistently less accurate (5-14% decrease). CONCLUSIONS: The results of our study suggest that compared with liver biopsy, non-invasive testing algorithms can result in short-term cost savings, but the consequences of misdiagnosis in terms of health outcomes and treatment costs might outweigh the short-term gains in cost and convenience.
Authors: U Siebert; G Sroczynski; S Rossol; J Wasem; U Ravens-Sieberer; B M Kurth; M P Manns; J G McHutchison; J B Wong Journal: Gut Date: 2003-03 Impact factor: 23.059
Authors: Keyur Patel; Stuart C Gordon; Ira Jacobson; Christophe Hézode; Esther Oh; Katie M Smith; Jean-Michel Pawlotsky; John G McHutchison Journal: J Hepatol Date: 2004-12 Impact factor: 25.083
Authors: Eric Zhang; Claire Wartelle-Bladou; Luigi Lepanto; Jean Lachaine; Guy Cloutier; An Tang Journal: Eur Radiol Date: 2015-05-21 Impact factor: 5.315
Authors: Harinder S Chahal; Elliot A Marseille; Jeffrey A Tice; Steve D Pearson; Daniel A Ollendorf; Rena K Fox; James G Kahn Journal: JAMA Intern Med Date: 2016-01 Impact factor: 44.409